Upload 4 files

.gitignore

@@ -0,0 +1,56 @@
+# These are some examples of commonly ignored file patterns.
+# You should customize this list as applicable to your project.
+# Learn more about .gitignore:
+#     https://www.atlassian.com/git/tutorials/saving-changes/gitignore
+
+# Node artifact files
+node_modules/
+dist/
+
+# Compiled Java class files
+*.class
+
+# Compiled Python bytecode
+*.py[cod]
+
+# Log files
+*.log
+
+# Package files
+*.jar
+
+# Maven
+target/
+dist/
+
+# JetBrains IDE
+.idea/
+
+# Unit test reports
+TEST*.xml
+
+# Generated by MacOS
+.DS_Store
+
+Thumbs.db
+
+# Applications
+*.app
+*.exe
+*.war
+
+# Large media files
+*.mp4
+*.tiff
+*.avi
+*.flv
+*.mov
+*.wmv
+
+.ipynb_checkpoints
+__pycache__
+*.egg-info
+.vscode/*
+.idea/*
+playground/
+# TinyLLaVABench

LICENCE

@@ -0,0 +1,202 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
+

README.md

@@ -1,13 +1,311 @@
----
-title: ADTinnyLLava
-emoji: 🌖
-colorFrom: yellow
-colorTo: pink
-sdk: gradio
-sdk_version: 4.25.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+<h2 align="center"> <a href="https://arxiv.org/abs/2402.14289">TinyLLaVA: A Framework of Small-scale Large Multimodal Models</a>
+
+<h5 align="center">
+
+[![hf_space](https://img.shields.io/badge/🤗-%20Open%20In%20HF-blue.svg)](https://huggingface.co/bczhou/TinyLLaVA-3.1B) [![arXiv](https://img.shields.io/badge/Arxiv-2402.14289-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2402.14289) [![License](https://img.shields.io/badge/License-Apache%202.0-yellow)](https://github.com/PKU-YuanGroup/MoE-LLaVA/blob/main/LICENSE) 
+
+
+## &#x1F389; News
+* **[2024.03.10]**  base recipe out!
+* **[2024.03.10]**  Finetune scripts out!
+* **[2024.02.25]**  Update evaluation scripts and docs!
+* **[2024.02.25]**  Data descriptions out. Release TinyLLaVA-1.5B and TinyLLaVA-2.0B!
+* **[2024.02.24]**  Example code on inference and model loading added!
+* **[2024.02.23]**  Evaluation code and scripts released!
+* **[2024.02.21]**  Creating the [TinyLLaVABench](https://github.com/DLCV-BUAA/TinyLLavaBench) repository on GitHub!
+* **[2024.02.21]**  Our paper: [TinyLLaVA: A Framework of Small-scale Large Multimodal Models](https://arxiv.org/abs/2402.14289) is out!
+* **[2024.01.11]**  Our fist model [TinyLLaVA-1.4B](https://huggingface.co/bczhou/tiny-llava-v1-hf) is out!
+
+## &#x231B; TODO
+- [ ] Add support for Ollama and llama.cpp.
+- [x] Developers' guide / How to build demo locally.
+- [x] Training and custom finetuning docs.
+- [x] Model Zoo descriptions.
+- [x] Examples and inference.
+- [x] Release code for training.
+- [x] Add descriptions for evaluation.
+- [x] Add descriptions for data preparation.
+- [x] Release TinyLLaVA-1.5B and TinyLLaVA-2.0B.
+- [x] Release TinyLLaVA-3.1B.
+- [x] Release the evaluation code and weights today(2024.2.23).
+### &#x1F525; High performance, but with fewer parameters
+
+- Our best model, TinyLLaVA-3.1B, achieves better overall performance against existing 7B models such as LLaVA-1.5 and Qwen-VL.
+
+## Contents
+
+- [Install](#x1f527-requirements-and-installation)
+- [Model Zoo](#x1f433-model-zoo)
+- [Demo](#Demo)
+- [Quick Start](#x1f527-quick-start)
+- [Run Inference](#x1f527-run-inference)
+- [Evaluation](#evaluation)
+- [Data](#data-preparation)
+- [Train](#train)
+- [Custom Finetune](#custom-finetune)
+
+
+## &#x1F527; Requirements and Installation
+
+We recommend the requirements as follows.
+
+1. Clone this repository and navigate to LLaVA folder
+```bash
+git clone https://github.com/DLCV-BUAA/TinyLLaVABench.git
+cd TinyLLaVABench
+```
+
+2. Install Package
+```Shell
+conda create -n tinyllava python=3.10 -y
+conda activate tinyllava
+pip install --upgrade pip  # enable PEP 660 support
+pip install -e .
+```
+
+3. Install additional packages for training cases
+```Shell
+pip install -e ".[train]"
+pip install flash-attn --no-build-isolation
+```
+### Upgrade to the latest code base
+
+```Shell
+git pull
+pip install -e .
+
+# if you see some import errors when you upgrade, please try running the command below (without #)
+# pip install flash-attn --no-build-isolation --no-cache-dir
+```
+
+## &#x1F433; Model Zoo
+### Legacy Model
+- [tiny-llava-hf](https://huggingface.co/bczhou/tiny-llava-v1-hf)
+
+### Pretrained Models
+- [TinyLLaVA-3.1B](https://huggingface.co/bczhou/TinyLLaVA-3.1B)
+- [TinyLLaVA-2.0B](https://huggingface.co/bczhou/TinyLLaVA-2.0B)
+- [TinyLLaVA-1.5B](https://huggingface.co/bczhou/TinyLLaVA-1.5B)
+
+### Model Details
+| Name          | LLM               | Checkpoint                                     | LLaVA-Bench-Wild | MME      | MMBench | MM-Vet | SQA-image | VQA-v2 | GQA   | TextVQA |
+|---------------|-------------------|------------------------------------------------|------------------|----------|---------|--------|-----------|--------|-------|---------|
+| TinyLLaVA-3.1B | Phi-2             | [TinyLLaVA-3.1B](https://huggingface.co/bczhou/TinyLLaVA-3.1B) | 75.8             | 1464.9   | 66.9    | 32.0   | 69.1      | 79.9   | 62.0  | 59.1    |
+| TinyLLaVA-2.0B | StableLM-2-1.6B   | [TinyLLaVA-2.0B](https://huggingface.co/bczhou/TinyLLaVA-2.0B) | 66.4             | 1433.8     | 63.3    | 32.6   | 64.7      | 78.9   | 61.9  | 56.4    |
+| TinyLLaVA-1.5B | TinyLlama         | [TinyLLaVA-1.5B](https://huggingface.co/bczhou/TinyLLaVA-1.5B) | 60.8             | 1276.5     | 55.2     | 25.8   | 60.3      | 76.9   | 60.3  | 51.7    |
+
+
+## Demo
+
+### Gradio Web Demo
+
+Launch a local web demo by running:
+```shell
+python tinyllava/serve/app.py --model-path bczhou/TinyLLaVA-3.1B --model-name TinyLLaVA-3.1B
+```
+
+### CLI Inference
+
+We also support running inference with CLI. To use our model, run:
+```shell
+python -m tinyllava.serve.cli \
+    --model-path bczhou/TinyLLaVA-3.1B \
+    --image-file "./tinyllava/serve/examples/extreme_ironing.jpg" 
+```
+
+
+## &#x1F527; Quick Start
+
+<details>
+<summary>Load model</summary>
+    
+```Python
+from tinyllava.model.builder import load_pretrained_model
+from tinyllava.mm_utils import get_model_name_from_path
+from tinyllava.eval.run_tiny_llava import eval_model
+
+model_path = "bczhou/TinyLLaVA-3.1B"
+
+tokenizer, model, image_processor, context_len = load_pretrained_model(
+    model_path=model_path,
+    model_base=None,
+    model_name=get_model_name_from_path(model_path)
+)
+```
+</details>
+
+## &#x1F527; Run Inference
+Here's an example of running inference with [TinyLLaVA-3.1B](https://huggingface.co/bczhou/TinyLLaVA-3.1B)
+<details>
+<summary>Run Inference</summary>
+    
+```Python
+from tinyllava.model.builder import load_pretrained_model
+from tinyllava.mm_utils import get_model_name_from_path
+from tinyllava.eval.run_tiny_llava import eval_model
+
+model_path = "bczhou/TinyLLaVA-3.1B"
+prompt = "What are the things I should be cautious about when I visit here?"
+image_file = "https://llava-vl.github.io/static/images/view.jpg"
+
+args = type('Args', (), {
+    "model_path": model_path,
+    "model_base": None,
+    "model_name": get_model_name_from_path(model_path),
+    "query": prompt,
+    "conv_mode": "phi",
+    "image_file": image_file,
+    "sep": ",",
+    "temperature": 0,
+    "top_p": None,
+    "num_beams": 1,
+    "max_new_tokens": 512
+})()
+
+eval_model(args)
+```
+</details>
+
+### Important
+We use different `conv_mode` for different models. Replace the `conv_mode` in `args` according to this table:
+| model          	| conv_mode 	|
+|----------------	|-----------	|
+| TinyLLaVA-3.1B 	| phi       	|
+| TinyLLaVA-2.0B 	| phi       	|
+| TinyLLaVA-1.5B 	| v1        	|
+
+## Evaluation
+To ensure the reproducibility, we evaluate the models with greedy decoding.
+
+See [Evaluation.md](https://github.com/DLCV-BUAA/TinyLLaVABench/blob/main/docs/Evaluation.md)
+
+## Data Preparation
+
+In our paper, we used two different datasets: the [LLaVA dataset](https://github.com/haotian-liu/LLaVA?tab=readme-ov-file#pretrain-feature-alignment) and the [ShareGPT4V dataset](https://github.com/InternLM/InternLM-XComposer/blob/main/projects/ShareGPT4V/docs/Data.md), and compared their differences. In this section, we provide information on data preparation.
+
+### Pretraining Images
+* LLaVA: The pretraining images of LLaVA is from the 558K subset of the LAION-CC-SBU dataset.
+* ShareGPT4V: The pretraining images of ShareGPT4V is a mixture of 558K LAION-CC-SBU subset, SAM dataset, and COCO dataset.
+
+### Pretraining Annotations
+* LLaVA: The pretraining annotations of LLaVA are [here](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain).
+* ShareGPT4V: The pretraining annotations of ShareGPT4V are [here](https://huggingface.co/datasets/Lin-Chen/ShareGPT4V/blob/main/share-captioner_coco_lcs_sam_1246k_1107.json).
+
+
+### SFT Images & Annotations
+The majority of the two SFT datasets are the same, with the exception that the 23K detailed description data in LLaVA-1.5-SFT being replaced with detailed captions randomly sampled from the [100K ShareGPT4V data](https://huggingface.co/datasets/Lin-Chen/ShareGPT4V/blob/main/sharegpt4v_instruct_gpt4-vision_cap100k.json).
+
+### Download data
+
+1. Download relevant images
+
+- LAION-CC-SBU-558K: [images.zip](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain/blob/main/images.zip)
+- COCO: This dataset is from the [COCO2017 challenge](https://cocodataset.org/). Download: [train2017](http://images.cocodataset.org/zips/train2017.zip)
+- WebData: This dataset is curated by the [ShareGPT4V project](https://github.com/InternLM/InternLM-XComposer/tree/main/projects/ShareGPT4V). Download: [images](https://drive.google.com/drive/folders/1tCUQ-sq6vdshZVkF0ZeF3K4eztkXJgax?usp=sharing). Only for academic usage.
+- SAM: This dataset is collected by [Meta](https://ai.meta.com/datasets/segment-anything-downloads/). Download: [images](https://ai.meta.com/datasets/segment-anything-downloads/). We only use 000000~000050.tar for now. If you just want to use ShareGPT4V for SFT, you can quickly download 9K images from [here](https://drive.google.com/file/d/1dKumdOKSXtV7lIXdrG7jsIK_z2vZv2gs/view?usp=drive_link).
+- GQA: [GQA project page](https://cs.stanford.edu/people/dorarad/gqa/about.html). Download: [images](https://downloads.cs.stanford.edu/nlp/data/gqa/images.zip)
+- OCR-VQA: [OCR-VQA project page](https://ocr-vqa.github.io/). Download: [download script](https://drive.google.com/drive/folders/1_GYPY5UkUy7HIcR0zq3ZCFgeZN7BAfm_?usp=sharing). We save all files as `.jpg`
+- TextVQA: [TextVQA project page](https://textvqa.org/). Download: [trainvalimages](https://dl.fbaipublicfiles.com/textvqa/images/train_val_images.zip)
+- VisualGenome: [VisualGenome project page](https://homes.cs.washington.edu/~ranjay/visualgenome/index.html). Download: [part1](https://cs.stanford.edu/people/rak248/VG_100K_2/images.zip), [part2](https://cs.stanford.edu/people/rak248/VG_100K_2/images2.zip)
+
+
+2. Download relevant annotations
+
+- LLaVA's pretraining annotations: [blip_laion_cc_sbu_558k.json](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain)
+- LLaVA's SFT annotations: [llava_v1_5_mix665k.json](https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/blob/main/llava_v1_5_mix665k.json)
+- ShareGPT4V's pretraining annotations: [share-captioner_coco_lcs_sam_1246k_1107.json](https://huggingface.co/datasets/Lin-Chen/ShareGPT4V/blob/main/share-captioner_coco_lcs_sam_1246k_1107.json)
+- ShareGPT4V's SFT annotations: [sharegpt4v_mix665k_cap23k_coco-ap9k_lcs3k_sam9k_div2k.json](https://huggingface.co/datasets/Lin-Chen/ShareGPT4V/blob/main/sharegpt4v_mix665k_cap23k_coco-ap9k_lcs3k_sam9k_div2k.json)
+
+
+### Organize Data
+
+Organize the image files and annotation files as follows in `path/to/your/data`:
+
+```none
+data
+├── llava
+│   ├── llava_pretrain
+│   │   ├── images
+│   │   ├── blip_laion_cc_sbu_558k.json
+├── coco
+│   ├── train2017
+├── sam
+│   ├── images
+├── gqa
+│   ├── images
+├── ocr_vqa
+│   ├── images
+├── textvqa
+│   ├── train_images
+├── vg
+│   ├── VG_100K
+│   ├── VG_100K_2
+├── share_textvqa
+│   ├── images
+├── web-celebrity
+│   ├── images
+├── web-landmark
+│   ├── images
+├── wikiart
+│   ├── images
+├── text_files
+│   ├── llava_v1_5_mix665k.json
+│   ├── share-captioner_coco_lcs_sam_1246k_1107.json
+│   ├── sharegpt4v_mix665k_cap23k_coco-ap9k_lcs3k_sam9k_div2k.json
+```
+
+## Train
+
+**This section we describe the base recipe.**
+### Hyperparameters
+Both hyperparameters used in pretraining and finetuning are provided below.
+
+1. Pretraining
+
+| Hyperparameter | Global Batch Size | Learning rate | Epochs | Max length | Weight decay |
+|----------------| ---: | ---: | ---: |-----------:| ---: |
+| TinyLLaVA-3.1B | 256 | 1e-3 | 1 |       3072 | 0 |
+
+2. Finetuning
+
+| Hyperparameter | Global Batch Size | Learning rate | Epochs | Max length | Weight decay |
+|----------------| ---: | ---: | ---: |-----------:| ---: |
+| TinyLLaVA-3.1B | 128 | 2e-5 | 1 |       3072 | 0 |
+
+### Pretrain
+
+**Replace paths to your paths**
+
+Training script with DeepSpeed ZeRO-2: [`pretrain.sh`](https://github.com/DLCV-BUAA/TinyLLaVABench/blob/main/scripts/tiny_llava/pretrain.sh).
+
+### Finetune
+
+**Replace paths to your paths**
+
+Training script with DeepSpeed ZeRO-3: [`finetune.sh`](https://github.com/DLCV-BUAA/TinyLLaVABench/blob/main/scripts/tiny_llava/finetune.sh).
+
+## Custom-Finetune
+
+Check out our custom finetune using LoRA [here](https://github.com/DLCV-BUAA/TinyLLaVABench/blob/dev/docs/CUTOM_FINETUNE.md).
+
+
+## &#x270F; Citation
+
+If you find our paper and code useful in your research, please consider giving a star :star: and citation :pencil:.
+
+```BibTeX
+@misc{zhou2024tinyllava,
+      title={TinyLLaVA: A Framework of Small-scale Large Multimodal Models}, 
+      author={Baichuan Zhou and Ying Hu and Xi Weng and Junlong Jia and Jie Luo and Xien Liu and Ji Wu and Lei Huang},
+      year={2024},
+      eprint={2402.14289},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG}
+}
+```
+
+
+## ❤️ Community efforts
+* Our codebase is built upon the [LLaVA](https://github.com/haotian-liu/LLaVA) project. Great work!
+* Our project uses data from the [ShareGPT4V](https://github.com/InternLM/InternLM-XComposer/tree/main/projects/ShareGPT4V) project. Great work!
+

pyproject.toml

@@ -0,0 +1,37 @@
+[build-system]
+requires = ["setuptools>=61.0"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "tinyllava"
+version = "1.0.0"
+description = "A Framework of Small-scale Large Multimodal Models."
+readme = "README.md"
+requires-python = ">=3.9"
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: OSI Approved :: Apache Software License",
+]
+dependencies = [
+    "torch==2.0.1", "torchvision==0.15.2", "tiktoken",
+    "transformers==4.37.2", "tokenizers==0.15.1", "sentencepiece==0.1.99", "shortuuid",
+    "accelerate==0.21.0", "peft==0.4.0", "bitsandbytes==0.41.0",
+    "pydantic<2,>=1", "markdown2[all]", "numpy", "scikit-learn==1.2.2",
+    "gradio==3.35.2", "gradio_client==0.2.9",
+    "requests", "httpx==0.23.3", "uvicorn", "fastapi",
+    "einops==0.6.1", "einops-exts==0.0.4", "timm==0.6.13",
+]
+
+[project.optional-dependencies]
+train = ["deepspeed==0.9.5", "ninja", "wandb"]
+
+[project.urls]
+"Homepage" = "https://github.com/DLCV-BUAA/TinyLLaVABench"
+"Bug Tracker" = "https://github.com/DLCV-BUAA/TinyLLaVABench/issues"
+
+[tool.setuptools.packages.find]
+exclude = ["assets*", "benchmark*", "docs", "dist*", "playground*", "scripts*", "tests*"]
+
+[tool.wheel]
+exclude = ["assets*", "benchmark*", "docs", "dist*", "playground*", "scripts*", "tests*"]
+